Case Studyros 2edge impulseyolo proembedded inference
Autonomous Quadruped Robot Tracks And Pursues Ball
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7.0
A project develops an autonomous legged robot that detects, tracks, and pursues a ball in real time using ROS 2, micro-ROS, and an Edge Impulse-trained model. The system uses a Hiwonder MechDog with an ESP32-S3 vision module and an Arduino Uno Q (Qualcomm Dragonwing QRB2210) for on-device inference; 182 labeled images trained a quantized YOLO‑Pro model achieving 99.2% precision and 100% test accuracy.
Scoring Rationale
Practical, reproducible robotics integration with on-device ML; limited novelty and single-project scope reduce broader impact.
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